Darwin, the intelligent machine benchmark, learns a virtual ideal process on the basis of high-frequency PLC data from several machines and thus provides a target value how fast each machine could be and how to get there. Based on this, Darwin continuously generates concrete recommendations for reducing the cycle time. Maintenance departments are empowered by Darwin to avoid breakdowns before they happen thanks to early warnings.
Analysis of machine processes on signal-level based on high frequency live data
Comparison of similar machines on a very detailed machine component level
Deduction of optimization actions for each real machine to reduce cycle times
Constant monitoring of machine sub-process behaviour with notification of anomalies for maintenance department
“With its continuously learning Darwin-Recommender technology plus10 has provided practical proof on several injection moulding machines that significant production increases in elastomer processing are possible in practice.”
Director Digital Business Development/Industrie 4.0
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